Applications of urinary proteomics in biomarker discovery

Urine is an important source of biomarkers. This article reviews current advances, major challenges, and future prospects in the field of urinary proteomics. Because the practical clinical problem is to distinguish diseases with similar symptoms, merely comparing samples from patients of a particular disease to those of healthy individuals is inadequate for finding biomarkers with sufficient diagnostic power. In addition, the variation of expression levels of urinary proteins among healthy individuals and individuals under different physiological conditions adds to the difficulty in identifying biomarkers. We propose that establishing the natural variation in urinary protein expression among a healthy population can serve as a reference to help identify protein abundance changes that are caused by disease, not by individual variations or physiological changes. We also discuss that comparing protein expression levels between urine and plasma may reveal the physiological function of the kidney and that may facilitate biomarker discovery. Finally, we propose that establishing a data-sharing platform for data collection and integrating results from all urinary biomarker studies will help promote the development of urinary proteomics.     

Proteomics of human cerebrospinal fluid: discovery and verification of biomarker candidates in neurodegenerative diseases using quantitative proteomics

There is an urgent need for novel biomarkers that can be used to improve the diagnosis, predict the disease progression, improve our understanding of the pathology or serve as therapeutic targets for neurodegenerative diseases. Cerebrospinal fluid (CSF) is in direct contact with the CNS and reflects the biochemical state of the CNS under different physiological and pathological settings. Because of this, CSF is regarded as an excellent source for identifying biomarkers for neurological diseases and other diseases affecting the CNS. Quantitative proteomics and sophisticated computational software applied to analyze the protein content of CSF has been fronted as an attractive approach to find novel biomarkers for neurological diseases. This review will focus on some of the potential pitfalls in biomarker studies using CSF, summarize the status of the field of CSF proteomics in general, and discuss some of the most promising proteomics biomarker study approaches. A brief status of the biomarker discovery efforts in multiple sclerosis, Alzheimer's disease, and Parkinson's disease is also given.     

Proteomics and its applications for biomarker discovery in human saliva

Human saliva is a biological fluid with enormous diagnostic potential. Because saliva can be non-invasively collected, it provides an attractive alternative for blood, serum or plasma. It has been postulated that the blood concentrations of many components are reflected in saliva. Saliva harbors a wide array of proteins, which can be informative for the detection of diseases. Profiling the proteins in saliva over the course of disease progression could reveal potential biomarkers indicative of different stages of diseases, which may be useful in medical diagnostics. With advanced instrumentation and developed refined analytical techniques, proteomics is widely envisioned as a useful and powerful approach for salivary proteomic biomarker discovery. As proteomic technologies continue to mature, salivary proteomics have great potential for biomarker research and clinical applications. The progress and current status of salivary proteomics and its application in the biomarker discovery of oral and systematic diseases will be reviewed. The scientific and clinical challenges underlying this approach will also be discussed.     

A web-based tool for in silico biomarker discovery based on tissue-specific protein profiles in normal and cancer tissues

Here we report the development of a publicly available Web-based analysis tool for exploring proteins expressed in a tissue- or cancer-specific manner. The search queries are based on the human tissue profiles in normal and cancer cells in the Human Protein Atlas portal and rely on the individual annotation performed by pathologists of images representing immunohistochemically stained tissue sections. Approximately 1.8 million images representing more than 3000 antibodies directed toward human proteins were used in the study. The search tool allows for the systematic exploration of the protein atlas to discover potential protein biomarkers. Such biomarkers include tissue-specific markers, cell type-specific markers, tumor type-specific markers, markers of malignancy, and prognostic or predictive markers of cancers. Here we show examples of database queries to generate sets of candidate biomarker proteins for several of these different categories. Expression profiles of candidate proteins can then subsequently be validated by examination of the underlying high resolution images. The present study shows examples of search strategies revealing several potential protein biomarkers, including proteins specifically expressed in normal cells and in cancer cells from specified tumor types. The lists of candidate proteins can be used as a starting point for further validation in larger patient cohorts using both immunological approaches and technologies utilizing more classical proteomics tools.     

Serial changes in urinary proteome profile of membranous nephropathy: implications for pathophysiology and biomarker discovery

Membranous nephropathy is one of the most common causes of primary glomerular diseases worldwide. The present study adopted a gel-based proteomics approach to better understand the pathophysiology and define biomarker candidates of human membranous nephropathy using an animal model of passive Heymann nephritis (PHN). Clinical characteristics of Sprague-Dawley rats injected with rabbit anti-Fx1A antiserum mimicked those of human membranous nephropathy. Serial urine samples were collected at Days 0, 10, 20, 30, 40, and 50 after the injection with anti-Fx1A (number of rats = 6; total number of gels = 36). Urinary proteome profiles were examined using 2D-PAGE and SYPRO Ruby staining. Quantitative intensity analysis and ANOVA with Tukey post-hoc multiple comparisons revealed 37 differentially expressed proteins among 6 different time-points. These altered proteins were successfully identified by MALDI-TOF MS and classified into 6 categories: (i) proteins with decreased urinary excretion during PHN; (ii) proteins with increased urinary excretion during PHN; (iii) proteins with increased urinary excretion during PHN, but which finally returned to basal levels; (iv) proteins with increased urinary excretion during PHN, but which finally declined below basal levels; (v) proteins with undetectable levels in the urine during PHN; and (vi) proteins that were detectable in the urine only during PHN. Most of these altered proteins have functional significance in signaling pathways, glomerular trafficking, and controlling the glomerular permeability. The ones in categories (v) and (vi) may serve as biomarkers for detecting or monitoring membranous nephropathy. After normalization of the data with 24-h urine creatinine excretion, changes in 34 of initially 37 differentially expressed proteins remained statistically significant. These data underscore the significant impact of urinary proteomics in unraveling disease pathophysiology and biomarker discovery.     

Using an Isolated Rat Kidney Model to Identify Kidney Origin Proteins in Urine

The use of targeted proteomics to identify urinary biomarkers of kidney disease in urine can avoid the interference of serum proteins. It may provide better sample throughput, higher sensitivity, and specificity. Knowing which urinary proteins to target is essential. By analyzing the urine from perfused isolated rat kidneys, 990 kidney origin proteins with human analogs were identified in urine. Of these proteins, 128 were not found in normal human urine and may become biomarkers with zero background. A total of 297 proteins were not found in normal human plasma. These proteins will not be influenced by other normal organs and will be kidney specific. The levels of 33 proteins increased during perfusion with an oxygen-deficient solution compared to those perfused with oxygen. The 75 proteins in the perfusion-driven urine have a significantly increased abundance ranking compared to their ranking in normal human urine. When compared with existing candidate biomarkers, over ninety percent of the kidney origin proteins in urine identified in this study have not been examined as candidate biomarkers of kidney diseases.     

Proteomics and its applications for biomarker discovery in human saliva

Human saliva is a biological fluid with enormous diagnostic potential. Because saliva can be non-invasively collected, it provides an attractive alternative for blood, serum or plasma. It has been postulated that the blood concentrations of many components are reflected in saliva. Saliva harbors a wide array of proteins, which can be informative for the detection of diseases. Profiling the proteins in saliva over the course of disease progression could reveal potential biomarkers indicative of different stages of diseases, which may be useful in medical diagnostics. With advanced instrumentation and developed refined analytical techniques, proteomics is widely envisioned as a useful and powerful approach for salivary proteomic biomarker discovery. As proteomic technologies continue to mature, salivary proteomics have great potential for biomarker research and clinical applications. The progress and current status of salivary proteomics and its application in the biomarker discovery of oral and systematic diseases will be reviewed. The scientific and clinical challenges underlying this approach will also be discussed.     

Recent advances in atherosclerosis-based proteomics: new biomarkers and a future perspective

Vascular proteomics is providing two main types of data: proteins that actively participate in vascular pathophysiological processes and novel protein candidates that can potentially serve as useful clinical biomarkers. Although both types of proteins can be identified by similar proteomic strategies and methods, it is important to clearly distinguish biomarkers from mediators of disease. A particular protein, or group of proteins, may participate in a pathogenic process but not serve as an effective biomarker. Alternatively, a useful biomarker may not mediate pathogenic pathways associated with disease (i.e., C-reactive protein). To date, there are no clear successful examples in which discovery proteomics has led to a novel useful clinical biomarker in cardiovascular diseases. Nevertheless, new sources of biomarkers are being explored (i.e., secretomes, circulating cells, exosomes and microparticles), an increasing number of novel proteins involved in atherogenesis are constantly described, and new technologies and analytical strategies (i.e., quantitative proteomics) are being developed to access low abundant proteins. Therefore, this presages a new era of discovery and a further step in the practical application to diagnosis, prognosis and early action by medical treatment of cardiovascular diseases.     

Introduction to proteomics: tools for the new biology

Towards revolutionary biomarkers, a considerable amount of research funds and time have been dedicated to proteomics. Although the discovery of novel biomarkers at the dawn of proteomics was a promising development, only a few identified biomarkers seemed to be beneficial for cancer patients. We may need to approach this issue differently, instead of only extending the conventional approaches that have been used historically. The study of biomarkers is essentially a study of diseases and the biochemistry relating to peptide, protein and post-translational modifications is only a tool. A problem-oriented approach should be needed in biomarker development. Clinician participation in the study of biomarkers will lead to realistic, practical and interesting biomarker candidates, which justify the time and expense involved in validation studies. Although discussion in this article is focused on cancer biomarkers, it can generally be applied to biomarker studies for other diseases.     

尿液蛋白质组作为下一代生物标志物的潜力

生物标志物是与机体生理及病理生理状态相关的可监测到变化的生化指标,尿液不属于内环境,没有稳态机制,能够积累并反映机体生理状态的早期变化,有潜力辅助疾病的早期诊断和预后监测。得益于非侵入性的收集方式,尿液可以被连续、大量、重复收集并便捷、稳定地保存,且组分相对简单,易于分析,是理想的标志物研究样本。但临床尿液样本蛋白质组可能会受到生活习惯、用药情况等多种混杂因素的影响,而动物模型方便控制变量,可以最大程度减少混杂因素的干扰,并使得在疾病发生、发展极早期采集样本成为可能;此外,患者的疾病分期、分型、用药情况等信息不能被忽视,现有样本策略和分析方式有待优化,例如,对同一个人不同时期、不同状态(例如患病前后)的尿液样本进行前后对照是一种理想的分析方式,这种方式能够消除个体间差异性的影响,符合个性化、精准化医疗的趋势;在无自身对照样本的情况下,一对多的分析方法能够更好地体现个体与健康群体的差别,辅助未知疾病的诊断和鉴别。尿液大分子的膜保存方式使得临床样本的保存更加简单经济。尿液生物标志物领域研究的进步需要政策和伦理的支持、资金和人力长期持续的投入以及大样本、大数据的辅助。本文综述了尿液生物标志物...     

Diagnostic function of the neuroinflammatory biomarker YKL-40 in Alzheimer’s disease and other neurodegenerative diseases

Introduction: Neuroinflammation is a crucial mechanism in the pathophysiology of neurodegenerative diseases pathophysiology. Cerebrospinal fluid (CSF) YKL-40 – an indicator of microglial activation ? has recently been identified by proteomic studies as a candidate biomarker for Alzheimer’s disease (AD).

Areas covered: We review the impact of CSF YKL-40 as a pathophysiological biomarker for AD and other neurodegenerative diseases. CSF YKL-40 concentrations have been shown to predict progression from prodromal mild cognitive impairment to AD dementia. Moreover, a positive association between CSF YKL-40 and other biomarkers of neurodegeneration – particularly total tau protein ? has been reported during the asymptomatic preclinical stage of AD and other neurodegenerative diseases. Albeit preliminary, current data do not support an association between APOE-ε4 status and CSF YKL-40 concentrations. When interpreting the diagnostic/prognostic significance of CSF YKL-40 concentrations in neurodegenerative diseases, potential confounders – including age, metabolic and cardiovascular risk factors, diagnostic criteria for selecting cases/controls – need to be considered.

Expert opinion/commentary: CSF YKL-40 represents a pathophysiological biomarker reflecting immune/inflammatory mechanisms in neurodegenerative diseases, associated with tau protein pathology. Besides being associated with tau pathology, CSF YKL-40 adds to the growing array of biomarkers reflecting distinct molecular brain mechanisms potentially useful for stratifying individuals for biomarker-guided, targeted anti-inflammatory therapies emerging from precision medicine.     

Serum and urinary biomarker signatures for rapid preclinical in vivo assessment of CDK inhibition as a therapeutic approach for PKD

Recent advances in understanding the molecular pathogenesis of polycystic kidney diseases (PKD) are being translated into promising treatments. Currently, a response to therapy in preclinical animal models of PKD can only be evaluated after several weeks of treatment. The availability of biomarkers for rapid efficacy assessment would greatly facilitate the drug development process. Here we applied SELDI-TOF technology to establish serum and urinary biomarker signatures associated with a rapid therapeutic response to cyclin dependent kinase (CDK) inhibitor roscovitine in the jck mouse model of PKD. A set of 74 serum and 56 urinary markers was identified in the group receiving chronic treatment over 5 weeks. This set was further screened for early efficacy biomarkers in acutely (3-5 days) treated animals with mild (26 days of age) and advanced disease (50 days of age). A third group with intermediate disease (33 days of age) received a single injection to monitor rapid changes in protein profiles within 4, 24 or 48 hours after drug administration. Multifactorial comparative analysis of the acutely treated groups identified a set of 20 urinary and 21 serum efficacy biomarkers. This biomarker signature provides a necessary tool for further assessment of CDK inhibitors as therapeutic agents for PKD.     

Secreted proteins as a fundamental source for biomarker discovery

The proteins secreted by various cells (the secretomes) are a potential rich source of biomarkers as they reflect various states of the cells at real time and at given conditions. To have accessible, sufficient and reliable protein markers is desirable as they mark various stages of disease development and their presence/absence can be used for diagnosis, prognosis, risk stratification and therapeutic monitoring. As direct analysis of blood/plasma, a common and noninvasive patient screening method, can be difficult for candidate protein biomarker identification, the alternative/complementary approaches are required, one of them is the analysis of secretomes in cell conditioned media in vitro. As the proteins secreted by cells as a response to various stimuli are most likely secreted into blood/plasma, the identification and pre-selection of candidate protein biomarkers from cell secretomes with subsequent validation of their presence at higher levels in serum/plasma is a promising approach. In this review, we discuss the proteins secreted by three progenitor cell types (smooth muscle, endothelial and cardiac progenitor cells) and two adult cell types (neonatal rat ventrical myocytes and smooth muscle cells) which can be relevant to cardiovascular research and which have been recently published in the literature. We found, at least for secretome studies included in this review, that secretomes of progenitor and adult cells overlap by 48% but the secretomes are very distinct among progenitor cell themselves as well as between adult cells. In addition, we compared secreted proteins to protein identifications listed in the Human Plasma PeptideAtlas and in two reports with cardiovascular-related proteins and we performed the extensive literature search to find if any of these secreted proteins were identified in a biomarker study. As expected, many proteins have been identified as biomarkers in cancer but 18 proteins (out of 62) have been tested as biomarkers in cardiovascular diseases as well.     

Protein biomarker validation via proximity ligation assays

The ability to detect minute amounts of specific proteins or protein modifications in blood as biomarkers for a plethora of human pathological conditions holds great promise for future medicine. Despite a large number of plausible candidate protein biomarkers published annually, the translation to clinical use is impeded by factors such as the required size of the initial studies, and limitations of the technologies used. The proximity ligation assay (PLA) is a versatile molecular tool that has the potential to address some obstacles, both in validation of biomarkers previously discovered using other techniques, and for future routine clinical diagnostic needs. The enhanced specificity of PLA extends the opportunities for large-scale, high-performance analyses of proteins. Besides advantages in the form of minimal sample consumption and an extended dynamic range, the PLA technique allows flexible assay reconfiguration. The technology can be adapted for detecting protein complexes, proximity between proteins in extracellular vesicles or in circulating tumor cells, and to address multiple post-translational modifications in the same protein molecule. We discuss herein requirements for biomarker validation, and how PLA may play an increasing role in this regard. We describe some recent developments of the technology, including proximity extension assays, the use of recombinant affinity reagents suitable for use in proximity assays, and the potential for single cell proteomics. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Towards proteome standards: The use of absolute quantitation in high-throughput biomarker discovery

The use of proteomics to profile biological fluids and identify therein biomarkers for cancer and other diseases was initially received with considerable excitement. However, results have fallen short of the expectations. Traditionally, protein biomarkers have been identified by measurement of relative expression changes between case and control samples from which differentially expressed proteins are then considered to represent biomarker candidates.We argue that current individual proteomics-based biomarker discovery studies lack the statistical strength for the identification of high-confidence biomarkers. Instead, multi-group efforts are necessary to facilitate the generation of sufficient sample sizes. This is contingent on the ability to collate and cross-compare data from different studies, which will require the use of a common metric or standards.Though profound, the technical challenges for absolute protein quantification can be overcome. The use of matrix specific, shared standards for absolute quantitation presents an opportunity to facilitate the much needed, but currently impossible, comparisons of different studies. In addition to community-wide approaches to standardize pre-analytical biomarker research studies, it is also important to establish means to integrate experimental data from different studies in order to assess the usefulness of proposed biomarkers with sufficient statistical certainty.     

Tissue proteomics for cancer biomarker development: laser microdissection and 2D-DIGE

Novel cancer biomarkers are required to achieve early diagnosis and optimized therapy for individual patients. Cancer is a disease of the genome, and tumor tissues are a rich source of cancer biomarkers as they contain the functional translation of the genome, namely the proteome. Investigation of the tumor tissue proteome allows the identification of proteomic signatures corresponding to clinico-pathological parameters, and individual proteins in such signatures will be good biomarker candidates. Tumor tissues are also a rich source for plasma biomarkers, because proteins released from tumor tissues may be more cancer specific than those from non-tumor cells. Two-dimensional difference gel electrophoresis (2D-DIGE) with novel ultra high sensitive fluorescent dyes (CyDye DIGE Fluor satulation dye) enables the efficient protein expression profiling of laser-microdissected tissue samples. The combined use of laser microdissection allows accurate proteomic profiling of specific cells in tumor tissues. To develop clinical applications using the identified biomarkers, collaboration between research scientists, clinicians and diagnostic companies is essential, particularly in the early phases of the biomarker development projects. The proteomics modalities currently available have the potential to lead to the development of clinical applications, and channeling the wealth of produced information towards concrete and specific clinical purposes is urgent.     

Proteomics approach and techniques in identification of reliable biomarkers for diseases

Biomarkers, also called biological markers, are indicators to identify a biological case or situation as well as detecting any presence of biological activities and processes. Proteins are considered as a type of biomarkers based on their characteristics. Therefore, proteomics approach is one of the most promising approaches in this field. The purpose of this review is to summarize the use of proteomics approach and techniques to identify proteins as biomarkers for different diseases. This review was obtained by searching in a computerized database. So, different researches and studies that used proteomics approach to identify different biomarkers for different diseases were reviewed. Also, techniques of proteomics that are used to identify proteins as biomarkers were collected. Techniques and methods of proteomics approach are used for the identification of proteins' activities and presence as biomarkers for different types of diseases from different types of samples. There are three essential steps of this approach including: extraction and separation of proteins, identification of proteins, and verification of proteins. Finally, clinical trials for new discovered biomarker or undefined biomarker would be on.     

Proteomic profiling of pancreatic cancer for biomarker discovery

Pancreatic cancer is a uniformly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. In recent years, there has been a substantial interest in applying proteomics technologies to identify protein biomarkers for early detection of cancer. Quantitative proteomic profiling of body fluids, tissues, or other biological samples to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers for the early diagnosis, therapeutic targets, and disease response markers. In this article, we discuss recent progress and challenges for applying quantitative proteomics technologies for biomarker discovery in pancreatic cancer.     

Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.     

Comparative profiling of serum glycoproteome by sequential purification of glycoproteins and 2-nitrobenzensulfenyl (NBS) stable isotope labeling: a new approach for the novel biomarker discovery for cancer

The recent progress in various proteomic technologies allows us to screen serum biomarker including carbohydrate antigens. However, only a limited number of proteins could be detected by current conventional methods such as shotgun proteomics, primarily because of the enormous concentration distribution of serum proteins and peptides. To circumvent this difficulty and isolate potential cancer-specific biomarkers for diagnosis and treatment, we established a new screening system consisting of the sequential steps of (1) immunodepletion of 6 high-abundance proteins, (2) targeted enrichment of glycoproteins by lectin column chromatography, and (3) the quantitative proteome analysis using 12C6- or 13C6-NBS (2-nitrobenzenesulfenyl) stable isotope labeling followed by MALDI-QIT-TOF mass spectrometric analysis. Through this systematic analysis for five serum samples derived from patients with lung adenocarcinoma, we identified as candidate biomarkers 34 serum glycoproteins that revealed significant difference in alpha1,6-fucosylation level between lung cancer and healthy control, clearly demonstrating that the carbohydrate-focused proteomics could allow for the detection of serum components with cancer-specific features. In addition, we developed a more simplified and practical technique, mass spectrometry-based glycan structure analysis and lectin blotting, in order to validate glycan structure of candidate biomarkers that could be applicable in clinical use. Our new glycoproteomic strategy will provide highly sensitive and quantitative profiling of specific glycan structures on multiple proteins, which should be useful for serum biomarker discovery.